{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 决策树的学习曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn import datasets\n",
    "\n",
    "boston = datasets.load_boston()\n",
    "X = boston.data\n",
    "y = boston.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=666)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 学习曲线"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "基于RMSE绘制学习曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "def plot_learning_curve(algo, X_train, X_test, y_train, y_test):\n",
    "    train_score = []\n",
    "    test_score = []\n",
    "    for i in range(2, len(X_train)+1):\n",
    "        algo.fit(X_train[:i], y_train[:i])\n",
    "    \n",
    "        y_train_predict = algo.predict(X_train[:i])\n",
    "        train_score.append(mean_squared_error(y_train[:i], y_train_predict))\n",
    "    \n",
    "        y_test_predict = algo.predict(X_test)\n",
    "        test_score.append(mean_squared_error(y_test, y_test_predict))\n",
    "        \n",
    "    plt.plot([i for i in range(2, len(X_train)+1)], \n",
    "                               np.sqrt(train_score), label=\"train\")\n",
    "    plt.plot([i for i in range(2, len(X_train)+1)], \n",
    "                               np.sqrt(test_score), label=\"test\")\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "    \n",
    "plot_learning_curve(DecisionTreeRegressor(), X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "基于R^2值绘制学习曲线"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import r2_score\n",
    "\n",
    "def plot_learning_curve_r2(algo, X_train, X_test, y_train, y_test):\n",
    "    train_score = []\n",
    "    test_score = []\n",
    "    for i in range(2, len(X_train)+1):\n",
    "        algo.fit(X_train[:i], y_train[:i])\n",
    "    \n",
    "        y_train_predict = algo.predict(X_train[:i])\n",
    "        train_score.append(r2_score(y_train[:i], y_train_predict))\n",
    "    \n",
    "        y_test_predict = algo.predict(X_test)\n",
    "        test_score.append(r2_score(y_test, y_test_predict))\n",
    "        \n",
    "    plt.plot([i for i in range(2, len(X_train)+1)], \n",
    "                               train_score, label=\"train\")\n",
    "    plt.plot([i for i in range(2, len(X_train)+1)], \n",
    "                               test_score, label=\"test\")\n",
    "    plt.legend()\n",
    "    plt.axis([0, len(X_train)+1, -0.1, 1.1])\n",
    "    plt.show()\n",
    "    \n",
    "plot_learning_curve_r2(DecisionTreeRegressor(), X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "以max_depth参数为例，看不同参数学习曲线的不同"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_learning_curve_r2(DecisionTreeRegressor(max_depth=1), X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_learning_curve_r2(DecisionTreeRegressor(max_depth=3), X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_learning_curve_r2(DecisionTreeRegressor(max_depth=5), X_train, X_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_learning_curve_r2(DecisionTreeRegressor(max_depth=20), X_train, X_test, y_train, y_test)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
